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Hi Matthew,

I'm a little late to the thread, but I thought I would still like to add
DPF3b, kindly provided by Wolfram Tempel. This dataset is available on
zenodo and forms the basis of a tutorial for using DIALS:
https://dials.github.io/documentation/tutorials/correcting_poor_initial_geometry_tutorial.html.
As the tutorial states,

This is a challenging dataset to process. There are a combination of
problems, including:

   - A ‘reversed’ rotation axis
   - Incorrect beam centre recorded in the image headers
   - Split spots
   - Multiple lattices
   - Systematically weak spots that may correspond to pseudocentring

Cheers
-- David


On Tue, 25 Sep 2018 at 18:27, Whitley, Matthew J <[log in to unmask]> wrote:

> Dear colleagues,
>
> I want to thank the following people for providing suggestions and
> comments about ‘difficult’ datasets suitable for teaching data processing:
>
> Tim Craig
> Jacob Keller
> Graeme Winter
> Aleksandar Bijelic
> Clemens Vonrhein
> Loes Kroon-Batenburg
> James Holton
>
> If anyone else has suggestions for good datasets for teaching processing,
> I would still be happy to hear them.
>
> Finally, several people asked me to make available a list of all the
> dataset suggestions I receive.  I am happy to do so, and I will post a
> message to this list when the information is up and available, probably
> later in the fall.
>
>
> Sincerely,
> Matthew
>
>
>
> ---
> Matthew J. Whitley, Ph.D.
> Research Instructor
> Department of Pharmacology & Chemical Biology
> University of Pittsburgh School of Medicine
>
>
>
>
> On 9/19/2018 5:15 PM, Whitley, Matthew J wrote:
>
> Dear colleagues,
>
> For teaching purposes, I am looking for a small number (< 5) of
> macromolecular diffraction datasets (raw images) that might be
> considered 'difficult' for a beginning crystallography student to
> process.  By 'difficult' I generally mean not able to be processed
> automatically by a common processing package (XDS, Mosflm, DIALS, etc)
> using default settings, i.e., no black box "click and done" processing.
> The datasets I am looking for would have some stumbling block such as
> incorrect experimental parameters recorded in the image headers,
> multiple lattices that cause indexing to fail, datasets for which
> determining the correct space group is tricky, datasets for experiments
> in which the crystal slipped or moved in the beam, or anything else you
> can think of.  The idea is for these beginning students to examine
> several datasets that highlight various phenomena that can lead one
> astray during processing.
>
> A good candidate dataset would also ideally comprise a modest number of
> images so as to keep integration time to a minimum.  Factors that are
> mostly irrelevant for my purpose: resolution (as long as better than
> ~3.5 Å), source (home vs synchrotron), presence/absence of anomalous
> scattering,  presence/absence of ligands, monomeric vs oligomeric
> structures, etc.  Also, to be clear, I am not looking for datasets that
> have so many pathologies that they would require many long hours of work
> for an expert to process correctly.
>
> I have checked public repositories such as proteindiffraction.org and
> SBGrid databank, but all of the datasets I acquired from these sources
> process satisfactorily with little effort, and in any event I know of no
> way to search for 'challenging' datasets.  (I also wonder whether
> anybody is in the habit of depositing, shall we say, less-than-pristine
> images to public repositories?)
>
> If you know of such a dataset that is already publicly available, or if
> you have such a dataset that you are willing to share for solely
> educational purposes, I would appreciate hearing from you, either on- or
> off-list.
>
> Thank you in advance for your suggestions.
>
> Matthew
>
>
>
>
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